• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.501-509
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• 2018

Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1837-1846
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• 2022

The annual increase in chemical accidents is causing damage to life and the environment due to the spread and residual of substances. Environmental damage investigation is more difficult to determine the geographical scope and timing than human damage investigation. Considering the reality that there is a lack of professional investigation personnel, it is urgent to develop an efficient quantitative evaluation method. In order to improve this situation, this paper conducted a chemical accidents investigation using unmanned aerial vehicles(UAV) equipped with various sensors. The damaged area was calculated by Ortho-image and strength of agreement was calculated using the normalized difference vegetation index image. As a result, the Cohen's Kappa coefficient was 0.649 (threshold 0.7). However, there is a limitation in that analysis has been performed based on the pixel of the normalized difference vegetation index. Therefore, there is a need for a chemical accident investigation plan that overcomes the limitations.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.462-466
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• 2006

Close-to-nature stream evaluation is one of the processing to make the streams over in order to keep them natural. It is integral to evaluate and make an accurate analysis of them on the purpose of maintaining streams healthy. For many instances, there are, stream organization evaluation for restoration by German government, evaluation for ecosystem protection in natural preserves by New Zealand government, and stream-view evaluation for restoration by Britain government so on. In case of the country there are analysis and evaluation of stream physical organization by Cho, Yong-hyun, Close-to-nature stream evaluation for restoration by Kim, Dong-chan, evaluation of stream properties in korea by Park, Bong-jin. Close-to-nature evaluation by Lim, Chan-uk, that is advanced version of Park, Bong-jin's, shows form of stream including waterway curve, sand bar, diversity of flow, river bed material, diversity of minor bed, minor bed bank protection works, bank protection material. It also does environment of stream including side of minor bed vegetation, width of surface of the water/width of the river etc.. By the way, this evaluation does not have free access to apply those details above in the field, it often happens that you get various outcome from the one spot. so you must need more realistic testing method to obtain more accurate data. Remote sensing method is highly recommended because this is very useful for collecting realistic data of vegetation index. what is more, it can not only scan even the minimum area within its resolving power but also do obtain data anytime. Vegetation index indicates Ratio vegetation index, Normalized difference vegetation index, Soil adjusted vegetation index, Atmospherically resistant vegetation index etc.. The research is focusing on Cheokgwa stream which is the branch of Taehwa river and shows 19 sectioned Close-to-nature stream performed according to the method by Lim, chan-uk. Besides let you know vegetation index came from image data of satellite landsat 7 with the variation of buffering area, of the day 9. may. 2003. Of all, the outcome 0.758 at 200m buffer-zone of NDVI was the best we have got so far.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.149-160
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• 2015

A comparative study was conducted for alternative consecutive procedures of detection of cloud-contaminated pixels and gap-filling and smoothing of time-series data to produce high-quality gapless satellite vegetation index (i.e. Normalized Difference Vegetation Index, NDVI). Performances of five alternative methods for detecting cloud contaminations were tested with ground-observed cloudiness data. The data gap was filled with a simple linear interpolation and then, it was applied two alternative smoothing methods (i.e. Savitzky-Golay and Wavelet transform). Moderate resolution imaging spectroradiometer (MODIS) data were used in this study. Among the alternative cloud detection methods, a criterion of MODIS Band 3 reflectance over 10% showed best accuracy with an agreement rate of 85%, which was followed by criteria of MODIS Quality assessment (82%) and Band 3 reflectance over 20% (81%), respectively. In smoothing process, the Savitzky-Golay filter was better performed to retain original NDVI patterns than the wavelet transform. This study demonstrated an operational framework of gapdetection, filling, and smoothing to produce high-quality satellite vegetation index.

• Journal of Wetlands Research
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• v.13 no.2
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• pp.171-179
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• 2011

The main objective of this study is to estimate of the vegetation response induced by climate change to soil moisture. We investigated a relationship between vegetation activity and climate variables using Moderate Resolution Imaging Spectroradiometer (MODIS)-retrieved Normalized Difference Vegetation Index (NDVI) and soil moisture. NDVI which extracted from MODIS 13 Vegetation Indices Product was considered as an useful parameter to figure out a relationship with two types of soil moisture, which were observed at Rural Development Administration sites and estimated from Advanced Microwave Scanning Radiometer E (AMSR-E) satellite imagery. The correlation of MODIS-NDVI and ground measured soil moisture were observed, became much stronger when compared to soil moisture values with time lag (5days, 10days, 15days). The correlation patterns between NDVI and soil moisture with different time lag were related to soil texture. The results from this study will be useful to understand the role of vegetation in water balance control in various scales from regional to global climate change.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.165-168
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• 2005

In this study, emissivity and land surface temperature (LST) were retrieved using the previously developed algorithms and Aqua/MODIS data. And sensitivity of estimated emissivity and LST to the predefined values, such as land cover, normalized difference vegetation index (NOVI) and spectral emissivity were investigated. The methods used for emissivity and LST were vegetation cover method (VCM) and four different split-window algorithms. The spectral emissivity retrieved by VCM was not sensitive to the NOVI error but more sensitive to the land cover error. The comparison of LST showed that the LST was systematically different without regard to the land cover and season. And the LST was very sensitive to the emissivity error excepting the Uliveri et al. This preliminary result indicates that more works are needed for the retrieval of reliable LST from satellite data.

• Spatial Information Research
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• v.20 no.4
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• pp.47-55
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• 2012

Normalized Difference Vegetation Index (NDVI) has been used to measure and monitor plant growth, vegetation cover, and biomass from multispectral satellite data. It is also a valuable index in forest applications, providing forest resource information. In this research, an approach for monitoring forest change using MODIS NDVI time series data is explored. NDVI difference-based approaches for a specific point in time have possible accuracy problems and are lacking in monitoring long-term forest cover change. It means that a multi-time NDVI pattern change needs to be considered. In this study, an efficient methodology to consider long-term NDVI pattern is suggested using a harmonic model. The suggested method reconstructs MODIS NDVI time series data through application of the harmonic model, which corrects missing and erroneous data. Then NDVI pattern is analyzed based on estimated values of the harmonic model. The suggested method was applied to 49 NDVI time series data from Aug. 21, 2009 to Sep. 6, 2011 and its usefulness was shown through an experiment.

• Journal of the Korean earth science society
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• v.27 no.6
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• pp.677-686
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• 2006

Surface evapotranspiration is one of the most important factors to determine the surface energy budget, and its estimation is strongly related with the accuracy of weather forecasting. Surface evapotranspiration over Daegu Metropolitan was estimated using high resolution LANDSAT TM data. The estimation of surface evapotranspiration is based on the relationship between surface radiative temperature and vegetation index provided by a TM sensor. The distribution of NDVI (Normalized Difference of Vegetation Index) corresponds well with that of land-used in Deagu Metropolitan. The temperature of several part of downtown in Deagu metropolitan is lower in comparison with the averaged radiative temperature. This is caused by the high evapotranspiration from dense vegetation like DooRyu Park in Deagu Metropolitan. But, weak evapotranspiration availability is distinguished over the central part of downtown and the difference of evapotranspiration availability on industrial complexes and residential area is also clear.

• Journal of Environmental Science International
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• v.25 no.12
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• pp.1653-1660
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• 2016

Drought is a reoccurring worldwide natural hazard that affects not only food production but also economics, health, and infrastructure. Drought monitoring is usually performed with precipitation-based indices without consideration of the actual state and amount of the land surface properties. A drought index based on the actual evapotranspiration can overcome these shortcomings. The severity of a drought can be quantified by making a spatial map. The procedure for estimating actual evapotranspiration is costly and complicated, and requires land surface information. The possibility of utilizing drone-driven remotely sensed data for actual evapotranspiration estimation was analyzed in this study. A drone collected data was used to calculate the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI). The spatial resolution was 10 m with a grid of $404{\times}395$. The collected data were applied and parameterized to an actual evapotranspiration estimation. The result shows that drone-based data is useful for estimating actual evapotranspiration and the corresponding drought indices.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.446-446
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• 2022

본 연구에서는 MODIS(MODerate resolution Imaging Spectroradiometer) 다중 위성영상을 기반으로 전국 시공간 토양수분 및 토양수분 기반의 가뭄지수 SWDI(Soil Water Deficit Index)를 산정하였다. 시공간 토양수분의 산정을 위해 입력자료로 MODIS 위성의 지표면온도(Land Surface Temperature, LST), 증발산 및 식생(Enhanced Vegetation Index, EVI; Fraction of Photosynthetically Active Radiation, FPAR; Leaf Area Index, LAI; Normalized Difference Vegetation Index, NDVI) 관련 산출물 자료와 지상 관측자료인 일 단위 강수량 자료를 구축하였다. MODIS 위성영상은 산출물별로 제공되는 QC(Quality Control) 영상을 활용해 보정을 수행하였고, 공간 강수량 자료는 기상청에서 제공하는 전국 92개 지점의 종관기상관측자료를 구축하여 공간보간기법인 역거리가중법을 적용해 생성하였다. 실측 토양수분은 농촌진흥청에서 제공하는 76개 지점의 토양 깊이 10 cm에 설치된 TDR(Time Domain Reflectomerty) 센서에서 측정된 토양수분 자료를 활용하였으며, 토양수분 모의 시 토양 속성을 고려하기 위해 국립농업과학원에서 제공하는 토양도를 구축하여 활용하였다. 토양수분 산정 모형은 다중선형회귀모형(Multiple Linear Regression Model, MLRM)을 활용하였으며, 계절 및 토성에 따른 회귀식을 산정하였다. 회귀식 기반의 토양수분과 토성별 포장용수량 및 영구위조점 값을 이용하여 SWDI를 산정하고, 실제 가뭄 발생 시기 및 지역과의 비교하고자 한다.